Kinari Nishiura,Eun-Hye Choi,Eunjong Choi,Osamu Mizuno
Kinari Nishiura,Eun-Hye Choi,Eunjong Choi,Osamu Mizuno
Kinari Nishiura,Eun-Hye Choi,Eunjong Choi,Osamu Mizuno
946
1.9 (2022)
Software Quality Journal
0
0
Two Improving Approaches for Faulty Interaction Localization using Logistic Regression Analysis
9999
Eunjong Choi,Norihiro Yoshida,Yoshiki Higo,Katsuro Inoue
Eunjong Choi,Norihiro Yoshida,Yoshiki Higo,Katsuro Inoue
Eunjong Choi,Norihiro Yoshida,Yoshiki Higo,Katsuro Inoue
803
IEICE Transactions on Information and Systems
2
2
0
Proposing and Evaluating Clone Detection Approaches with Preprocessing Input Source Files
E98-D
2015
Osamu Mizuno,Naoki Kawashima,Kimiaki Kawamoto
Prediction of fault-prone modules is an important area of software engineering. The authors assumed that the occurrence of faults is related to the semantics in the source code modules. Semantics in a software module can be extracted from identifiers in the module. Identifiers such as variable names and function names in source code are thus essential information to understand code. The naming for identifiers affects on code understandability; thus, the authors expect that they affect software quality. In this study, the authors examine the relationship between the length of identifiers and existence of software faults in a software module. Furthermore, the authors analyze the relationship between occurrence of “words” in identifiers and the existence of faults. From the experiments using the data from open source software, the authors modeled the relationship between the fault occurrence and the length of identifiers, and the relationship between the fault occurrence and the word in identifiers by the random forest technique. The result of the experiment showed that the length of identifiers can predict the fault-proneness of the software modules. Also, the result showed that the word occurrence model is as good a measure as traditional CK and LOC metrics models.
Osamu Mizuno,Naoki Kawashima,Kimiaki Kawamoto
Osamu Mizuno,Naoki Kawashima,Kimiaki Kawamoto
691
ACIS International Journal of Software Innovation
1
1
36-49
0
Fault-prone Module Prediction Approaches Using Identifiers in Source Code
DOI: 10.4018/ijsi.2015010103
3
2015
Osamu Mizuno,Hideaki Hata
In order to assure the quality of software product, early detection of fault-prone products is necessary. Fault-prone module detection is one of the major and traditional area of software engineering. However, comparative study using the fair environment rarely conducted so far because there is little data publicly available. This paper tries to conduct a comparative study of fault-prone module detection approaches.
Osamu Mizuno,Hideaki Hata
Osamu Mizuno,Hideaki Hata
Proc. of 34th Annual IEEE Computer Software and Applications Conference (COMPSAC2010)
615
7
Seoul, Korea
248-249
1
An Empirical Comparison of Fault-prone Module Detection Approaches: Complexity Metrics and Text Feature Metrics
2010